How the Zeo sleep device works around the limitations of home monitoring

is part of a trend toward using technology to monitor our own bodies.
People have always been concerned about their health, of course, and
have tried different things to see what works (including rather absurd
superstitions). But now there are ways to bolster one’s curiosity with
real scientific data.


The Zeo makes this data available for people
who may have sleep problems–and quite a lot do, judging from a

2005 National Sleep Foundation (NSF) poll

(a recent poll covering a wide range of adults):

26% say they had “a good night’s sleep” only a few nights a month or
less. Another 24% report having “a good night’s sleep” a few nights a

This blog is meant to be a technical discussion, not a consumer guide,
so I took the opportunity to talk to Ben Rubin, CTO and cofounder of Zeo, just a couple weeks
after the official release of the Zeo to get some information on two

  • How it collects data during sleep

  • How they analyze the data to help the customer sleep better

The Zeo sensor device is a simple headband with a silver layer that
lies on your forehead. The designers chose silver because it doesn’t cause
allergic reactions and efficiently picks up electronic waves with
minimal noise from sweat or other interference.

The electrical signals given off by the brain, the eyes, and muscle
movements around the face are collected 128 times per second.
Activity at different frequencies indicates what kind of sleep you’re
in (if any), in ways well known to sleep researchers. For instance:

  • Activity in the 11 to 14 Hz range indicate some form of sleep. Spikes
    in that range–sleep spindles–indicate light sleep.

  • Activity in the 2-4 Hz range (Delta waves) indicate deep sleep.

  • REM sleep has less in the Delta range and more in higher frequencies,
    along with the heightened eye movements that give the sleep phase its
    name, and fewer muscle contractions, which can be measured by activity
    in the 30 Hz range.

And so forth. The headband knows the essential frequencies of
electronic activity in the brain, in the eyes (because they’re
electronically polarized) and in the facial muscles. This is quite
impressive when you look at traditional sleep labs. They put sensors
on many different parts of the face to get their data. In contrast,
the Zeo picks up a signal that it has to separate into frequency
bands. Of course, the lab is more accurate, but its cost makes it
feasible only for diagnosed sleep disorders. (The Zeo company wants to
make it clear that they aren’t providing a medical device and don’t
offer diagnoses.)

Samples are run through a Fast Fourier Transform and more complex,
proprietary algorithms every 30 seconds to get data that the Zeo
device on your bedstand accumulates. It can tell you later how many
hours you spent in each phase of sleep. Every five minutes, another
calculation determines what phase you’re in (light, REM, deep, or
awake) and displays a band on an LED screen so you can check the
pattern of your sleep when you wake up. (In the figure, the bands indicating heaviness of sleep appear near the bottom of the screen.)

(Update, December 22: Zeo developers have posted

more detail about the timing of data collection

ZEO_FRONT_8 32_ZQ73.jpg

The calculations used by the Zeo were developed through a neural
network trained on huge numbers of people, both normal sleepers and
troubled sleepers. In effect, the algorithms were refined by comparing
their output to the analysis of sleep experts for each person who
joined the experiment. (Rubin was one of the guinea pigs, along with
many other staff. That was probably the most sleep any of them got
during their work in this start-up.)

Zeo ran an experiment in which sleepers were simultaneously monitored
by a prototype of the Zeo, by an older technology called an actigraph,
and by sleep researchers using a polysomnograph. The calculations by
the Zeo prototype came fairly close to the accuracy of the other forms
of measurement. For instance, the machine agreed with researchers
about 75% of the time about the difference between light sleep, REM
sleep, and deep sleep. This looks pretty good when you learn that the
two sleep researchers agreed with each other 85% of the time.

[Update, December 11, 2009: Rubin, in a comment, has posted the

research studies

from which I took those statistics.]

The goal of marketing the Zeo, of course, is to help people benefit
from their new knowledge. Typically, a customer records sleep for a
week, along with information about his lifestyle and related
information (such as whether family members woke him up). Zeo offers
a web site where customers can record this data, which was developed
through partnerships with the world’s leading sleep researchers and
consists of fairly standard questions: Are you stressed? Did you drink
caffeine or alcohol in the evening? How do you feel when you first
wake up?

The web site processes the data and makes recommendations, based on
well-understood findings in the field of sleep research, about what
you can change to improve to sleep. Another program you can sign up
for–Sleep Coach–compares the personal behavior you report with your
sleep patterns and makes more targeted recommendations.

Naturally, technologically sophisticated users want to get their hands
on their own data. Zeo has responded by offering customers
data–starting yesterday–in a CSV format. And there’s no reason that
people can’t share their data in order to search for new patterns in a
crowdsourcing manner, like the well-known

Our new sensitivity to health issues is sure to draw in companies with
technological solutions.
WIRED Magazine
profiled the Nike+
sensor and Internet recording system, and a company named
recently announced a WiFi-primed body weight scale that records your
weight, body fat content, and BMI to a web site (rather slim benefits
for $160, it seems to me).
Someday we may even be able to monitor many of the medical signs that
currently require blood work through

a device placed on the eye

These, along with Zeo, are examples where instant feedback and the
ability to track trends over time can change our whole attitude toward
our bodies. Fitness is no fad; we are recognizing the serious effects
lifestyle can have on our long-term happiness and ultimately our
economic output. Going deeper, it’s about time that computer
technology, which for so long has kept us immobile in our chairs and
divorce us from the physical world, made a 180° turn to put us
more in touch with our bodies and the reality around us.

So far as the Zeo goes, I pondered the value of the data it offers
when you’re considering life style choices. Do you really need a
machine to push you into giving up coffee or turning off the TV
earlier in the evening?

I think data can help, because different people are affected by
lifestyle decisions in different ways. There’s no reason to kick the
dog out of your bedroom or give up that cherished glass of Chianti you
have with your lasagna dinner if it really isn’t bothering you. That’s
the value of feedback: we can link our behavior to an outcome and make
rational choices. It’s easier to act healthy if you know you’re not
just being superstitious.

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